Experiment Configuration and Tracking

Interactive Explorer 2

Explore key concepts interactively

Parameters

Quick Check

Key concept question for section 2?

Option A

Option B

Option C

Correction:

Option B

This is the correct answer because it captures the core concept.

Common Mistake: Common Mistake in Section 2

Mistake:

Overlooking a critical implementation detail.

Correction:

Always verify results against known benchmarks and theoretical predictions.

Key Term 2

Core concept from section 2 of chapter 44.

Definition:
MLflow Experiment Tracking

MLflow logs parameters, metrics, and artifacts:

import mlflow
with mlflow.start_run():
    mlflow.log_param('lr', 1e-3)
    mlflow.log_metric('psnr', 32.5)
    mlflow.log_artifact('reconstruction.png')

Definition:
Reproducibility Checklist

A reproducible experiment requires:

Fixed random seeds
Pinned dependency versions
Logged hyperparameters
Version-controlled code
Stored model checkpoints

Theorem: PSNR Limitations

PSNR does not correlate well with perceptual quality: two images with the same PSNR can look vastly different. Always report multiple metrics (PSNR, SSIM, LPIPS).

Metrics Implementation Reproducibility